Complaints management
ISCO-08 4222, 4419Complaints handler, Customer complaints officer, Customer relations officer, Ombudsman liaison officer, Complaints manager
Headcount need, in FTE
Target AI skills
level 1 to 4Job skills
Growing in value
- Handling escalated and emotionally charged complaints
- Legal reasoning on contract terms
- Root cause analysis of recurring complaints
- Preparing files for the ombudsman
Losing value
- Sorting and qualifying incoming complaints
- Drafting standard acknowledgements and replies
- Retrieving file history across systems
- Tracking regulatory response deadlines
How the job will change
AI already sorts incoming complaints by subject and urgency, retrieves the policy, claim and contact history, and drafts a reasoned reply that the handler only needs to check. Simple complaints, such as a late reimbursement or a billing error, can be resolved in a few minutes instead of a day spent searching across systems.
Handlers keep the complaints where tone and judgement matter: a refused claim after a serious loss, a vulnerable customer, a threat of legal action, a case heading to the ombudsman. The job also moves towards analysing recurring causes and feeding them back to claims, sales and product teams. A good handler tomorrow writes with care and reasons clearly on contract terms.
- 2026-2027
- Automatic sorting of complaints, AI-drafted replies checked by handlers.
- 2028-2030
- Simple complaints resolved almost automatically, teams focus on sensitive cases.
- 2031+
- Smaller teams combining sensitive cases and root cause analysis.
Regulators watch how insurers treat complaints, especially from vulnerable customers. Over-automating replies risks standardised answers that miss the real grievance and push more cases to the ombudsman. See the seniority outlook below.
What if you hired fewer juniors?
Your 2036 seniors are the juniors you hire today.
Advanced settings modified
2026 2036
The AI Cookbook 2026
albert's guide to cut through the noise around generative AI and turn it into workforce decisions.
- What AI actually changes in jobs and skills
- Why the junior pipeline matters more than most companies realise
- How to integrate AI into workforce planning

Run these scenarios on your actual workforce
AI Impact Diagnostic: 6 to 8 weeks, your data in albert, three costed scenarios and the projected seniority mix for each job family.
How the numbers are built
Every headcount figure combines four assumptions. Three come pre-filled from public research and job family defaults. The strategic ceiling is yours to set.
Seniority outlook
A flow model with three levels of experience in the profession. Promotion and exit rates are set so that today's mix stays stable when hiring does not change: any gap you see comes from the junior hiring cut alone.
Sources
- International Labour OrganizationGenerative AI and jobs: a refined global index of occupational exposure (2025)
- ILO datasetTask-level GenAI exposure scores by ISCO-08 occupation
- AnthropicAnthropic Economic Index (June 2026 release, April and May 2026 usage data)
- Stanford Digital Economy LabCanaries in the Coal Mine? Six facts about the recent employment effects of AI